Skip to main content
SpringerLink
Log in

Coverage-All Targets Algorithm for 3D Wireless Multimedia Sensor Networks Based on the Gravitational Search Algorithm

  • Published:
Automatic Control and Computer Sciences Aims and scope Submit manuscript

Abstract

Aiming at the actual targets coverage scene of targets and sensors in the three-dimensional physical world, in order to use the minimal sensors to cover all the targets, a new coverage-all targets algorithm based on Gravitational Search algorithm (GSA-CT) is proposed. Firstly, from the practical point of view, a 3D coverage-all targets model of WMSNs which based on the spatial position relationship of sensors and targets is established in three-dimensional space. Secondly, in order to avoid randomness of the current order method to determine the minimal number of sensors to cover all the targets, a new fitness calculation method has been proposed. Thirdly, in order to improve solution accuracy, GSA is used as the optimization method of coverage-all targets method. Experimental results show that compared with the other 7 coverage methods for the 9 actual coverage scenarios, the number of sensors required for GSA-CT proposed in this paper is the least, and the method is very stable.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.
Fig. 7.
Fig. 8.
Fig. 9.
Fig. 10.
Fig. 11.

Similar content being viewed by others

REFERENCES

  1. Demir, A.K., Demiray, H.E., and Baydere, S., QoSMOS: Cross-layer QoS architecture for wireless multimedia sensor networks, Wireless Networks, 2014, vol. 20, no. 4, pp. 655–670.

    Article  Google Scholar 

  2. Chen, C.-C., Mukhopadhyay, S.C., Chuang, C.-L., et al., A hybrid memetic framework for coverage optimization in wireless sensor networks, IEEE Trans. Cybern., 2017, vol. 45, no. 10, pp. 2309–2322.

    Article  Google Scholar 

  3. Zhou, Y., Xiang, W., and Wang, G., Frame loss concealment for multiview video transmission over wireless multimedia sensor networks, IEEE Sens. J., 2015, vol. 15, no. 3, pp. 1892–1901.

    Article  Google Scholar 

  4. Lu, Y., Zhou, J., and Wan, L., C., Improved method for 2D target coverage in Wireless Sensor Networks, J. Xidian Univ., 2019, vol. 46, no. 2, pp. 101–106.

    Google Scholar 

  5. Sun, S., Sun, L., and Chen, S., Method of deployment and coverage for wireless sensor networks in three dimensional environment, J. Jilin Univ., 2016, vol. 54, no. 5, pp. 1109–1116.

    MATH  Google Scholar 

  6. Fan, X.G., Wang, H., and Hao, X., Algorithm for enhancing coverage ratio in directional sensor networks, Chin. J. Sci. Instrum., 2017, vol. 8, no. 2, pp. 368–377.

    Google Scholar 

  7. Tan, L., Wang, Y.H., Yang, M.H., et al., Three-dimensional space self-deployment algorithm based on virtual force compensation, Chin. J. Sci. Instrum., 2015, vol. 36, no. 11, pp. 2570–2578.

    Google Scholar 

  8. Ma, H., Zhang, X., and Ming, A., A coverage-enhancing method for 3D directional sensor networks, INFOCOM.IEEE, 2009, pp. 2791–2795.

    Google Scholar 

  9. Zhang, L.J. and Lin, F., Coverage strategy based on genetic algorithm for WSN, Commun. Technol., 2017, vol. 50, no. 5, pp. 962–967.

    Google Scholar 

  10. Manju, Chand, S., and Kumar, B., Target coverage heuristic based on learning automata in wireless sensor networks, IET Wireless Sens. Syst., 2018, vol. 8, no. 3, pp. 109–115.

    Article  Google Scholar 

  11. Wang, Y.J., Bi, X.J., Teng, Z.J., et al., Coverage-all targets algorithm of directional sensor network for three-dimensional perception, J. Jilin Univ. (Eng. Technol. Ed.), 2015, vol. 45, no. 5, pp. 1671–1679.

  12. Minárová, M., Paternain, D., Jurio, A., et al., Modifying the gravitational search algorithm: A functional study, Inf. Sci., 2018, vol. 430, no. 3, pp. 87–103.

    Article  MathSciNet  Google Scholar 

  13. Fan, Q., Wang, W., and Yan, X., Differential evolution algorithm with strategy adaptation and knowledge-based control parameters, Artif. Intell. Rev., 2017, vol. 51, no. 2, pp. 219–253.

    Article  Google Scholar 

Download references

Funding

This work was supported in part by the National Natural Science Foundation of China under grants no. 61501107, and the Education Department of Jilin province science and technology research project of “13th Five-Year” under grants [2016] no. 95. And the Project of Scientific and Technological Innovation Development of Jilin nos. 201750219 and 201750227.

Author information

Authors and Affiliations

  1. College of Electrical Engineering, Northeast Electric Power University, 132000, Jilin, China

    Yanjiao Wang &  Ye Chen

Authors
  1. Yanjiao Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ye Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Yanjiao Wang or Ye Chen.

Ethics declarations

The authors declare that they have no conflicts of interest.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yanjiao Wang, Ye Chen Coverage-All Targets Algorithm for 3D Wireless Multimedia Sensor Networks Based on the Gravitational Search Algorithm. Aut. Control Comp. Sci. 53, 429–440 (2019). https://doi.org/10.3103/S0146411619050109

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3103/S0146411619050109

Keywords:

Search

Navigation